PCA, CCA, and ANN Modeling of Climate and Land-Use Effects on Stream Water Quality of Karst Watershed in Upper Green River, Kentucky
Publication: Journal of Hydrologic Engineering
Volume 25, Issue 6
Abstract
Climate and land-use impacts on stream water quality in a karst watershed were studied to determine how they might be useful to model stream water quality parameter (SWQP) distribution from diffuse source pollution. This was achieved using principal component analysis (PCA), canonical correlation analysis (CCA), and artificial neural networks (ANNs) for the Upper Green River Watershed, Kentucky. Correlation analysis and eigenvalue analysis gave rise to what are known as effective input parameters for the subsequent ANN modeling. The results of ANN modeling indicated that although land-use contributions were better correlated when they were combined with temperature and precipitation for some of the SWQPs, most of the SWQP distribution trends were better predicted using the field data of temperature and precipitation at the watershed scale. This was in contrast to the findings of the many nonkarst watersheds where SWQPs showed a significant dependence on land use alone according to the literature. This, in essence, implies that the land-use influences are secondary, and precipitation and temperature affect the Upper Green River karst watershed’s SWQPs primarily, whereas for nonkarst watersheds the land use influences SWQPs primarily from diffuse source pollution.
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Data Availability Statement
All data used during the study were provided by a third party. Direct requests for these materials may be made to the provider as indicated in the Acknowledgments.
Acknowledgments
The authors sincerely thank Dr. Ouida Meier, Tim Rink (GIS Analyst), Jenna Harbaugh (GIS Analyst), and Dr. Stuart Foster, Director of Kentucky Climate Center, Western Kentucky University (WKU) for the data. The authors also thank Prof. Albert J. Meier and Prof. Chris Groves of WKU for fruitful, encouraging discussions. The authors also thank the Council of Scientific and Industrial Research (CSIR), India, for Grant No. 24(0356)/19/EMR-II of the project Experimental and Computational Studies of Surface Water Quality Parameters from Morphometry and Spectral Characteristics.
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Journal of Hydrologic Engineering
Volume 25 • Issue 6 • June 2020
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©2020 American Society of Civil Engineers.
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Received: May 1, 2019
Accepted: Dec 13, 2019
Published online: Apr 9, 2020
Published in print: Jun 1, 2020
Discussion open until: Sep 9, 2020
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